www.pudn.com > HMM1.zip > logist2Fit.m

function [beta, p] = logist2Fit(y, x, addOne, w) 
% LOGIST2FIT 2 class logsitic classification 
% function beta = logist2Fit(y,x, addOne) 
% 
% y(i) = 0/1 
% x(:,i) = i'th input - we optionally append 1s to last dimension 
% w(i) = optional weight 
% 
% beta(j)- regression coefficient 
 
if nargin < 3, addOne = 1; end 
if nargin < 4, w = 1; end 
 
Ncases = size(x,2); 
if Ncases ~= length(y) 
  error(sprintf('size of data = %dx%d, size of labels=%d', size(x,1), size(x,2), length(y))) 
end 
if addOne 
  x = [x; ones(1,Ncases)]; 
end 
[beta, p] = logist2(y(:), x', w(:)); 
beta = beta(:);